generating consistently high-quality and accurately labeled data through various methods to facilitate the training of NLP algorithms.
Natural Language Processing with Deep Learning
gain the skills to move from word representation and syntactic processing to
designing and implementing complex deep learning models for
question answering, machine translation, and other language understanding tasks
- Design, implement, and understand your NLP neural network models, using the Pytorch framework.
- Deep learning with pytorch tutorial
create datasets for model training, benchmarking, and overall advancemen
- Represent word meaning with word vectors, such as Word2Vec, SVD and GloVe.
- Identify semantic relationships between words in a sentence with dependency parsing.
- Make large scale word predictions with language models, recurrent neural networks (RNNs), and neural machine translation.
- Improve your NLP models and pretrain your transformers for more efficient natural language processing and understanding.
No comments:
Post a Comment